Authors
Bradley Jones (1), Ryan Lekivetz (1), Dibyen Majumdar (2), Christopher Nachtsheim (3) and Jonathan Stallrich (4)
Affiliations
(1) JMP Statistical Discovery LLC
(2) Department of Mathematics, Statistics, and Computer Science, University of Illinois, Chicago, Chicago, IL
(3) Carlson School of Management, University of Minnesota, Minneapolis, MN
(4) North Carolina State University, Raleigh, NC
Journal
Technometrics
Date Published
2020
Abstract
In this article, we propose a new method for constructing supersaturated designs that is based on the Kronecker product of two carefully chosen matrices. The construction method leads to a partitioning of the factors of the design such that the factors within a group are correlated to the others within the same group, but are orthogonal to any factor in any other group. We refer to the resulting designs as group-orthogonal supersaturated designs. We leverage this group structure to obtain an unbiased estimate of the error variance, and to develop an effective, design-based model selection procedure. Simulation results show that the use of these designs, in conjunction with our model selection procedure enables the identification of larger numbers of active main effects than have previously been reported for supersaturated designs. The designs can also be used in group screening; however, unlike previous group-screening procedures, with our designs, main effects in a group are not confounded. Supplementary materials for this article are available online.
Citation
Jones, B., Lekivetz, R., Majumdar, D., Nachtsheim, C.J. and Stallrich, J.W., 2020. Construction, properties, and analysis of group-orthogonal supersaturated designs. Technometrics, 62(3), pp.403-414, https://doi.org/10.1080/00401706.2019.1654926.